class_docstr: Base class for hooks based on summary metrics.
  
  Subclasses should override _process_metrics.
  
  If _process_metrics returns True, calls run_context.request_stop().
  
  This can be used to something like "Stop after the loss has stopped decreasing
  for 5000 steps.
code: def after_create_session(self, session, coord):
      del coord
      if self._start_step is None:
          self._start_step = session.run(self._global_step_tensor)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import tensorflow.compat.v1
  from tensorboard.backend.event_processing import event_accumulator
  from tensorboard.backend.event_processing import event_multiplexer
label_desc: Use image node_id 4 for calling the MetricsBasedHook obj's underlying member method code with example usage: obj.after_create_session(session, coord) without return types